In conventional marking devices, quality defects appear in a marked image due to various factors. For example, changes in the optical density introduced by differences in laser/LED bar intensities, subsystem non-uniformities, donor roll reload, and the like can lead to image quality defects. Additionally, spatial non-uniformity errors, e.g., a situation in which pixels in one part of an image that have been defined as a certain color appear different from pixels in another part of the image that have been defined as the same color, are also present. Wire history, wire contamination, charging subsystem variations and photoreceptor variations are among the root causes for spatial non-uniformity errors in images.
Spatial non-uniformity errors can be addressed by modifying hardware or hardware operations. For example, in LED bars, exposure variations can-be minimized by measuring the output of the LED elements and adjusting their duty cycle and/or intensity to ensure that all the elements have the same output. In laser exposure systems, similar duty cycle adjustments can be performed to minimize the exposure-related non-uniformities. Furthermore, routine cleaning of wires to remove contamination helps to reduce wire history-related non-uniformities.
Modifying hardware or hardware operations results in added downtime, which often translates into lost revenues. Moreover, since image quality defects of various types often occur together (e.g., banding, streaking, mottle, macro and micro non-uniformity, etc.), it is often the case that by optimizing the system to address one type of defect usually results in amplifying one or more of the other types of defects. In addition to image quality defects often colors are not consistent. A solution to this problem has already been disclosed in U.S. application Ser. No. 09/566,291 entitled: On-Line Calibration System For A Dynamically Varying Color Marking Device. Therein, a color marking device including a control system for calibration of the device based upon dynamic color balance control of an output image is disclosed comprising a front end converter for converting an input signal representative of a target image having a pre-selected color into a device-dependent control signal in accordance with a device TRC, a color marking device for outputting an output image in response to the control signal, a sensor for measuring a parameter from the output image representative of a color of the output image, and, a point-wise controller for comparing the parameter with a corresponding parameter from the target image and constructing adjusted controlled points for the device TRC when the measured parameter and the corresponding parameter vary by a pre-selected value, a color balance controller for constructing an adjusted device TRC from the controlled points, whereby subsequently generated output images are output with the adjusted device TRC and, more accurately represent target input images.
However, additional problems have arisen. In principle, printing equal amounts of cyan, magenta and yellow should produce a specific neutral gray. Instead, printers generally make a chromatic gray (a*,b*≠0) rather than a neutral gray. The printer will not produce a specific neutral gray due to limitations on the color pigments of the primaries and on the processes of the print engine. To overcome this last effect, gray balanced TRCs are used as LUTs to modulate the proportions of cyan, magenta and yellow depending on the state of the materials and of the print engine. For gray balancing printers, spectrophotometers are often used as sensors because gray is a mix of cyan, magenta and yellow primaries. Sensor to sensor differences are likely to result in differences in quality among prints across a plurality of differing print machines. Thus, what is also needed in this art is a method to account for sensor to sensor differences due to errors in spectral reconstruction algorithms such that sensor-to-sensor variations among different machines can be eliminated and overall machine-to-machine variations (i.e., sensor mounting variations, etc.) are reduced.